Job Description
Join Nexus Quantum Dynamics at the forefront of 2026's technological revolution. We're pioneering quantum-AI convergence systems that will redefine computational boundaries. As a Quantum AI Research Engineer, you'll architect hybrid quantum-neural networks that solve previously intractable problems in drug discovery, climate modeling, and cryptography. Our state-of-the-art lab offers access to 1000+ qubit processors and collaborate with Nobel laureates to transform theoretical breakthroughs into real-world applications.
This role combines deep quantum physics expertise with machine learning innovation. You'll develop error-correction protocols for quantum-AI hybrids, design fault-tolerant algorithms, and contribute to our open-source quantum framework. We offer competitive equity, flexible remote options, and an annual innovation retreat in Switzerland.
Responsibilities
- Design and implement quantum-AI hybrid algorithms for high-complexity optimization problems
- Develop quantum error-correction protocols for neural network integration
- Create fault-tolerant quantum machine learning models using 1000+ qubit systems
- Lead cross-functional teams in prototyping quantum-AI applications for healthcare and logistics
- Publish breakthrough research in Nature Physics and IEEE journals
- Optimize quantum neural networks for real-time inference on hybrid classical-quantum hardware
- Contribute to open-source quantum-AI frameworks used by Fortune 500 partners
Qualifications
- PhD in Quantum Computing, Physics, or Machine Learning (or equivalent experience)
- Expertise in quantum circuit design and quantum machine learning frameworks (Qiskit, Cirq, PennyLane)
- 3+ years developing AI models for high-dimensional optimization problems
- Proficiency in Python, C++, and quantum assembly languages
- Published research in quantum computing or AI at top-tier conferences
- Experience with quantum annealing and superconducting qubit systems
- Strong background in tensor networks and quantum information theory